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Ligandability and druggability assessment via machine learning

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Effects of Conformational Dynamics on Predicted Protein Druggability

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Binding MOAD (Mother Of All Databases)

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Highly accurate method for ligand‐binding site prediction in unbound state (apo) protein structures

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Druggability predictions: methods, limitations, and applications

inferredcites →https://doi.org/10.1002/wcms.1651openalex-snapshot

Graph neural networks for conditional de novo drug design

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The Automatic Search for Ligand Binding Sites in Proteins of Known Three-dimensional Structure Using only Geometric Criteria

inferredcites →https://doi.org/10.1007/978-0-387-78189-1openalex-snapshot

Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning

inferredcites →https://doi.org/10.1007/978-0-387-84858-7openalex-snapshot

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

inferredcites →https://doi.org/10.1007/978-1-4939-2486-8_7openalex-snapshot

Site Identification by Ligand Competitive Saturation (SILCS) Simulations for Fragment-Based Drug Design

inferredcites →https://doi.org/10.1007/978-3-319-21233-3_4openalex-snapshot

P2RANK: Knowledge-Based Ligand Binding Site Prediction Using Aggregated Local Features

inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot

U-Net: Convolutional Networks for Biomedical Image Segmentation

inferredcites →https://doi.org/10.1007/bf00994018openalex-snapshot

Support-Vector Networks

inferredcites →https://doi.org/10.1016/0263-7855(95)00073-9openalex-snapshot

SURFNET: A program for visualizing molecular surfaces, cavities, and intermolecular interactions

inferredcites →https://doi.org/10.1016/j.cag.2022.07.005openalex-snapshot

SHREC 2022: Protein–ligand binding site recognition

inferredcites →https://doi.org/10.1016/j.chembiol.2014.08.013openalex-snapshot

Oral Druggable Space beyond the Rule of 5: Insights from Drugs and Clinical Candidates

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Lead- and drug-like compounds: the rule-of-five revolution

inferredcites →https://doi.org/10.1016/j.drudis.2011.02.002openalex-snapshot

Fragment screening to predict druggability (ligandability) and lead discovery success

inferredcites →https://doi.org/10.1016/j.ejmech.2022.114614openalex-snapshot

Novel fragment-derived colchicine-site binders as microtubule-destabilizing agents

inferredcites →https://doi.org/10.1016/j.jmb.2012.11.041openalex-snapshot

Impact of Mutations on the Allosteric Conformational Equilibrium

inferredcites →https://doi.org/10.1016/j.jmb.2016.01.029openalex-snapshot

CryptoSite: Expanding the Druggable Proteome by Characterization and Prediction of Cryptic Binding Sites

inferredcites →https://doi.org/10.1016/j.jmb.2019.05.024openalex-snapshot

Updates to Binding MOAD (Mother of All Databases): Polypharmacology Tools and Their Utility in Drug Repurposing

inferredcites →https://doi.org/10.1016/j.molonc.2013.06.001openalex-snapshot

Through the open door: Preferential binding of dasatinib to the active form of BCR‐ABL unveiled by in silico experiments

inferredcites →https://doi.org/10.1021/acs.jcim.1c00204openalex-snapshot

Finding Druggable Sites in Proteins Using TACTICS

inferredcites →https://doi.org/10.1021/acs.jcim.1c00799openalex-snapshot

DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks

inferredcites →https://doi.org/10.1021/acs.jcim.1c01512openalex-snapshot

PointSite: A Point Cloud Segmentation Tool for Identification of Protein Ligand Binding Atoms

inferredcites →https://doi.org/10.1021/acs.jcim.2c01413openalex-snapshot

SiteRadar: Utilizing Graph Machine Learning for Precise Mapping of Protein–Ligand-Binding Sites

inferredcites →https://doi.org/10.1021/acs.jcim.6b00623openalex-snapshot

Deciphering Cryptic Binding Sites on Proteins by Mixed-Solvent Molecular Dynamics

inferredcites →https://doi.org/10.1021/acs.jcim.7b00650openalex-snapshot

K DEEP : Protein–Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks

inferredcites →https://doi.org/10.1021/acs.jcim.9b01185openalex-snapshot

Druggability Assessment in TRAPP Using Machine Learning Approaches

inferredcites →https://doi.org/10.1021/acs.jcim.9b01209openalex-snapshot

PlayMolecule CrypticScout: Predicting Protein Cryptic Sites Using Mixed-Solvent Molecular Simulations

inferredcites →https://doi.org/10.1021/acs.jctc.8b00263openalex-snapshot

Exploring Cryptic Pockets Formation in Targets of Pharmaceutical Interest with SWISH

inferredcites →https://doi.org/10.1021/acs.jctc.8b01295openalex-snapshot

Cosolvent-Enhanced Sampling and Unbiased Identification of Cryptic Pockets Suitable for Structure-Based Drug Design

inferredcites →https://doi.org/10.1021/acs.jmedchem.2c01577openalex-snapshot

Trends in Molecular Properties, Bioavailability, and Permeability across the Bayer Compound Collection

inferredcites →https://doi.org/10.1021/acs.jpcb.6b03515openalex-snapshot

Moving Beyond Active-Site Detection: MixMD Applied to Allosteric Systems

inferredcites →https://doi.org/10.1021/acscentsci.7b00211openalex-snapshot

Allosteric Communication Networks in Proteins Revealed through Pocket Crosstalk Analysis

inferredcites →https://doi.org/10.1021/cc9800071openalex-snapshot

A Knowledge-Based Approach in Designing Combinatorial or Medicinal Chemistry Libraries for Drug Discovery. 1. A Qualitative and Quantitative Characterization of Known Drug Databases

inferredcites →https://doi.org/10.1021/ci050372xopenalex-snapshot

sc-PDB: an Annotated Database of Druggable Binding Sites from the Protein Data Bank

inferredcites →https://doi.org/10.1021/ci1000289openalex-snapshot

Large-Scale Comparison of Four Binding Site Detection Algorithms

inferredcites →https://doi.org/10.1021/ci100241yopenalex-snapshot

Analyzing the Topology of Active Sites: On the Prediction of Pockets and Subpockets

inferredcites →https://doi.org/10.1021/ci100312topenalex-snapshot

Drug-like Density: A Method of Quantifying the “Bindability” of a Protein Target Based on a Very Large Set of Pockets and Drug-like Ligands from the Protein Data Bank

inferredcites →https://doi.org/10.1021/ci200266dopenalex-snapshot

DrugPred: A Structure-Based Approach To Predict Protein Druggability Developed Using an Extensive Nonredundant Data Set

inferredcites →https://doi.org/10.1021/ci200454vopenalex-snapshot

Combining Global and Local Measures for Structure-Based Druggability Predictions

inferredcites →https://doi.org/10.1021/ci300184xopenalex-snapshot

Comparison and Druggability Prediction of Protein–Ligand Binding Sites from Pharmacophore-Annotated Cavity Shapes

inferredcites →https://doi.org/10.1021/ci4000294openalex-snapshot

TRAPP: A Tool for Analysis ofTransient BindingPockets inProteins

inferredcites →https://doi.org/10.1021/ci5006004openalex-snapshot

PockDrug: A Model for Predicting Pocket Druggability That Overcomes Pocket Estimation Uncertainties

inferredcites →https://doi.org/10.1021/ci800324mopenalex-snapshot

Identifying and Characterizing Binding Sites and Assessing Druggability

inferredcites →https://doi.org/10.1021/ci9000053openalex-snapshot

Comparative Assessment of Scoring Functions on a Diverse Test Set

inferredcites →https://doi.org/10.1021/ct300117jopenalex-snapshot

Druggability Assessment of Allosteric Proteins by Dynamics Simulations in the Presence of Probe Molecules

inferredcites →https://doi.org/10.1021/ct501072topenalex-snapshot

A Collective Variable for the Rapid Exploration of Protein Druggability

inferredcites →https://doi.org/10.1021/ja1079332openalex-snapshot

Full Protein Flexibility Is Essential for Proper Hot-Spot Mapping

inferredcites →https://doi.org/10.1021/jacs.6b05425openalex-snapshot

Understanding Cryptic Pocket Formation in Protein Targets by Enhanced Sampling Simulations

inferredcites →https://doi.org/10.1021/jm00145a002openalex-snapshot

A computational procedure for determining energetically favorable binding sites on biologically important macromolecules

inferredcites →https://doi.org/10.1021/jm020017nopenalex-snapshot

Molecular Properties That Influence the Oral Bioavailability of Drug Candidates

inferredcites →https://doi.org/10.1021/jm049131ropenalex-snapshot

Druggability Indices for Protein Targets Derived from NMR-Based Screening Data

inferredcites →https://doi.org/10.1021/jm061277yopenalex-snapshot

Diverse, High-Quality Test Set for the Validation of Protein−Ligand Docking Performance

inferredcites →https://doi.org/10.1021/jm100574mopenalex-snapshot

Understanding and Predicting Druggability. A High-Throughput Method for Detection of Drug Binding Sites

inferredcites →https://doi.org/10.1021/jm801385dopenalex-snapshot

Binding Site Detection and Druggability Index from First Principles

inferredcites →https://doi.org/10.1038/nature06526openalex-snapshot

Reaching for high-hanging fruit in drug discovery at protein–protein interfaces

inferredcites →https://doi.org/10.1038/nbt1273openalex-snapshot

Structure-based maximal affinity model predicts small-molecule druggability

inferredcites →https://doi.org/10.1038/s41467-023-36699-3openalex-snapshot

Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network

inferredcites →https://doi.org/10.1038/s41570-022-00451-0openalex-snapshot

Rules were made to be broken

inferredcites →https://doi.org/10.1038/s41598-020-61860-zopenalex-snapshot

Improving detection of protein-ligand binding sites with 3D segmentation

inferredcites →https://doi.org/10.1038/s42003-020-01350-0openalex-snapshot

Spatiotemporal identification of druggable binding sites using deep learning

inferredcites →https://doi.org/10.1038/srep09179openalex-snapshot

Rsite: a computational method to identify the functional sites of noncoding RNAs

inferredcites →https://doi.org/10.1038/srep19016openalex-snapshot

Rsite2: an efficient computational method to predict the functional sites of noncoding RNAs

inferredcites →https://doi.org/10.1056/nejmoa1002315openalex-snapshot

Dasatinib versus Imatinib in Newly Diagnosed Chronic-Phase Chronic Myeloid Leukemia

inferredcites →https://doi.org/10.1073/pnas.141230798openalex-snapshot

Protacs: Chimeric molecules that target proteins to the Skp1–Cullin–F box complex for ubiquitination and degradation

inferredcites →https://doi.org/10.1074/jbc.m115.672048openalex-snapshot

Structural and Functional Characterization of the JH2 Pseudokinase Domain of JAK Family Tyrosine Kinase 2 (TYK2)

inferredcites →https://doi.org/10.1074/mcp.m400159-mcp200openalex-snapshot

Pocketome via Comprehensive Identification and Classification of Ligand Binding Envelopes

inferredcites →https://doi.org/10.1080/17460441.2017.1264385openalex-snapshot

Drug discovery beyond the rule of 5 - Opportunities and challenges

inferredcites →https://doi.org/10.1080/17460441.2021.1948997openalex-snapshot

Evolution of the drug-target residence time model

inferredcites →https://doi.org/10.1093/bioinformatics/btaa1091openalex-snapshot

The iPPI-DB initiative: a community-centered database of protein–protein interaction modulators

inferredcites →https://doi.org/10.1093/bioinformatics/btaa1092openalex-snapshot

Recognition of small molecule–RNA binding sites using RNA sequence and structure

inferredcites →https://doi.org/10.1093/bioinformatics/btab009openalex-snapshot

DeepSurf: a surface-based deep learning approach for the prediction of ligand binding sites on proteins

inferredcites →https://doi.org/10.1093/bioinformatics/btab849openalex-snapshot

InDeep: 3D fully convolutional neural networks to assist in silico drug design on protein–protein interactions

inferredcites →https://doi.org/10.1093/bioinformatics/bti315openalex-snapshot

Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites

inferredcites →https://doi.org/10.1093/bioinformatics/btr120openalex-snapshot

sc-PDB: a database for identifying variations and multiplicity of ‘druggable’ binding sites in proteins

inferredcites →https://doi.org/10.1093/bioinformatics/btr331openalex-snapshot

Identification of cavities on protein surface using multiple computational approaches for drug binding site prediction

inferredcites →https://doi.org/10.1093/bioinformatics/btr550openalex-snapshot

MDpocket: open-source cavity detection and characterization on molecular dynamics trajectories

inferredcites →https://doi.org/10.1093/bioinformatics/bts310openalex-snapshot

DoGSiteScorer: a web server for automatic binding site prediction, analysis and druggability assessment

inferredcites →https://doi.org/10.1093/bioinformatics/btt447openalex-snapshot

Protein–ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment

inferredcites →https://doi.org/10.1093/bioinformatics/btu626openalex-snapshot

PDB-wide collection of binding data: current status of the PDBbind database

inferredcites →https://doi.org/10.1093/bioinformatics/btx350openalex-snapshot

DeepSite: protein-binding site predictor using 3D-convolutional neural networks

inferredcites →https://doi.org/10.1093/bioinformatics/bty345openalex-snapshot

RBind: computational network method to predict RNA binding sites

inferredcites →https://doi.org/10.1093/bioinformatics/bty374openalex-snapshot

Development and evaluation of a deep learning model for protein–ligand binding affinity prediction

inferredcites →https://doi.org/10.1093/bioinformatics/bty583openalex-snapshot

LigVoxel: inpainting binding pockets using 3D-convolutional neural networks

inferredcites →https://doi.org/10.1093/bioinformatics/bty761openalex-snapshot

NanoShaper–VMD interface: computing and visualizing surfaces, pockets and channels in molecular systems

inferredcites →https://doi.org/10.1093/nar/gkac389openalex-snapshot

PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures

inferredcites →https://doi.org/10.1093/nar/gkm839openalex-snapshot

LigASite a database of biologically relevant binding sites in proteins with known apo-structures

inferredcites →https://doi.org/10.1093/nar/gkm911openalex-snapshot

Binding MOAD, a high-quality protein ligand database

inferredcites →https://doi.org/10.1093/nar/gkp281openalex-snapshot

SITEHOUND-web: a server for ligand binding site identification in protein structures

inferredcites →https://doi.org/10.1093/nar/gkq383openalex-snapshot

fpocket: online tools for protein ensemble pocket detection and tracking

inferredcites →https://doi.org/10.1093/nar/gkr356openalex-snapshot

DEPTH: a web server to compute depth and predict small-molecule binding cavities in proteins

inferredcites →https://doi.org/10.1093/nar/gks1002openalex-snapshot

2P2Idb: a structural database dedicated to orthosteric modulation of protein–protein interactions

inferredcites →https://doi.org/10.1093/nar/gks372openalex-snapshot

COFACTOR: an accurate comparative algorithm for structure-based protein function annotation

inferredcites →https://doi.org/10.1093/nar/gkt503openalex-snapshot

Depth: a web server to compute depth, cavity sizes, detect potential small-molecule ligand-binding cavities and predict the pKa of ionizable residues in proteins

inferredcites →https://doi.org/10.1093/nar/gku1088openalex-snapshot

Recent improvements to Binding MOAD: a resource for protein–ligand binding affinities and structures

inferredcites →https://doi.org/10.1093/nar/gku928openalex-snapshot

sc-PDB: a 3D-database of ligandable binding sites—10 years on

inferredcites →https://doi.org/10.1093/nar/gku972openalex-snapshot

The role of nucleobase interactions in RNA structure and dynamics

inferredcites →https://doi.org/10.1093/nar/gkv462openalex-snapshot

PockDrug-Server: a new web server for predicting pocket druggability on holo and apo proteins

inferredcites →https://doi.org/10.1093/nar/gky380openalex-snapshot

CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction

inferredcites →https://doi.org/10.1093/nar/gkz424openalex-snapshot

PrankWeb: a web server for ligand binding site prediction and visualization

inferredcites →https://doi.org/10.1093/nargab/lqab111openalex-snapshot

Structure-based deep learning for binding site detection in nucleic acid macromolecules

inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/iccv48922.2021.01595openalex-snapshot

Point Transformer

inferredcites →https://doi.org/10.1109/icdm.2008.17openalex-snapshot

Isolation Forest

inferredcites →https://doi.org/10.1109/tcsvt.2018.2869680openalex-snapshot

LDS-Inspired Residual Networks

inferredcites →https://doi.org/10.1109/tnnls.2016.2547220openalex-snapshot

Import Vector Domain Description: A Kernel Logistic One-Class Learning Algorithm

inferredcites →https://doi.org/10.1126/science.271.5251.997openalex-snapshot

Ligand Binding: Molecular Mechanics Calculation of the Streptavidin-Biotin Rupture Force

inferredcites →https://doi.org/10.1142/s0219720019500264openalex-snapshot

Glycine-induced formation and druggability score prediction of protein surface pockets

inferredcites →https://doi.org/10.1182/blood-2006-02-004580openalex-snapshot

Comparison of imatinib mesylate, dasatinib (BMS-354825), and nilotinib (AMN107) in an N-ethyl-N-nitrosourea (ENU)–based mutagenesis screen: high efficacy of drug combinations

inferredcites →https://doi.org/10.1186/1471-2105-10-168openalex-snapshot

Fpocket: An open source platform for ligand pocket detection

inferredcites →https://doi.org/10.1186/1471-2105-13-s4-s17openalex-snapshot

Identification of binding pockets in protein structures using a knowledge-based potential derived from local structural similarities

inferredcites →https://doi.org/10.1186/1472-6807-6-19openalex-snapshot

LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation.

inferredcites →https://doi.org/10.1186/s13321-015-0059-5openalex-snapshot

Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features

inferredcites →https://doi.org/10.1186/s13321-017-0255-6openalex-snapshot

Systematic exploration of multiple drug binding sites

inferredcites →https://doi.org/10.1186/s13321-018-0285-8openalex-snapshot

P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure

inferredcites →https://doi.org/10.1186/s13321-021-00547-7openalex-snapshot

PUResNet: prediction of protein-ligand binding sites using deep residual neural network

inferredcites →https://doi.org/10.1186/s13321-021-00570-8openalex-snapshot

Chemical toxicity prediction based on semi-supervised learning and graph convolutional neural network

inferredcites →https://doi.org/10.1186/s13321-022-00594-8openalex-snapshot

Improving the performance of models for one-step retrosynthesis through re-ranking

inferredcites →https://doi.org/10.1371/journal.pcbi.1000435openalex-snapshot

Computational Fragment-Based Binding Site Identification by Ligand Competitive Saturation

inferredcites →https://doi.org/10.1371/journal.pcbi.1000585openalex-snapshot

Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure

inferredcites →https://doi.org/10.1371/journal.pone.0059744openalex-snapshot

A general and Robust Ray-Casting-Based Algorithm for Triangulating Surfaces at the Nanoscale

inferredcites →https://doi.org/10.1371/journal.pone.0160315openalex-snapshot

Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

inferredcites →https://doi.org/10.14800/rd.544openalex-snapshot

Towards de novo RNA 3D Structure Prediction

inferredcites →https://doi.org/10.1517/17460441003677725openalex-snapshot

The dynamics of drug-target interactions: drug-target residence time and its impact on efficacy and safety

inferredcites →https://doi.org/10.2174/1381612811319120019openalex-snapshot

Binding Site Detection and Druggability Prediction of Protein Targets for Structure- Based Drug Design

inferredcites →https://doi.org/10.3389/fchem.2019.00873openalex-snapshot

In silico Methods for Design of Kinase Inhibitors as Anticancer Drugs

inferredcites →https://doi.org/10.3389/fddsv.2021.728469openalex-snapshot

Post-Pandemic Drug Discovery and Development: Facing Present and Future Challenges

inferredcites →https://doi.org/10.3389/fgene.2021.690049openalex-snapshot

Graph Neural Networks and Their Current Applications in Bioinformatics

inferredcites →https://doi.org/10.3389/fphar.2022.870479openalex-snapshot

Probabilistic Pocket Druggability Prediction via One-Class Learning

inferredcites →https://doi.org/10.3390/molecules27051496openalex-snapshot

Drug Design—Past, Present, Future

inferredcites →https://doi.org/10.3390/pharmaceutics15010119openalex-snapshot

CAT-Site: Predicting Protein Binding Sites Using a Convolutional Neural Network

inferredcites →https://doi.org/10.37349/etat.2020.00018openalex-snapshot

Current strategies for the design of PROTAC linkers: a critical review

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